Hourly Opening PriceThe Inner Circle Trader has noted that the Opening Price of every Hourly candle can be used in a Power Of 3 (PO3) context.
If Bullish, buy BELOW the hourly open.
If Bearish, sell ABOVE the hourly open.
The Power of 3 ICT model also know as "AMD" is a transformative trading strategy, ingeniously designed to streamline your time analyzing charts by focusing on three pivotal phases in market behavior: accumulation, manipulation, and distribution.
The ICT Power of Three Model dissects the market maker’s algorithm for price delivery into three pivotal actions: Accumulation, Manipulation, and Distribution. Accumulation involves smart money gathering positions before a price surge, while manipulation sees the market creating deceptive movements to trigger stops. Finally, distribution occurs as smart money offloads positions, often catching less informed traders off-guard. This strategy is a critical tool for traders to understand market makers’ maneuvers and to strategically position themselves in the market.
This indicator plots a line at the opening price of each hour and extends it on the chart for the duration of the hour. Each hour starts a new line.
You also have the option of extending the midnight opening price line across the entire trading day.
Komut dosyalarını "accumulation" için ara
Daye's Quarterly TheoryDaye's Quarterly Theory Indicator
Description
The Daye's Quarterly Theory Indicator divides trading time into smaller units to help traders identify potential accumulation, manipulation, distribution, and reversal/continuation phases within a day. It applies these time divisions to your charts, offering visual guidance aligned with ICT's PO3 concept:
Accumulation (A): The phase where positions are accumulated.
Manipulation (M): The phase where the market moves against the prevailing trend to trap traders.
Distribution (D): The phase where accumulated positions are distributed.
Reversal/Continuation (X): The phase indicating either a reversal or continuation of the trend.
This indicator breaks down time into quarters at different levels:
Daily Quarters:
Q1: 18:00 - 00:00 (Asia)
Q2: 00:00 - 06:00 (London)
Q3: 06:00 - 12:00 (NY AM)
Q4: 12:00 - 18:00 (NY PM)
90-Minute Quarters:
Q1: 18:00 - 19:30
Q2: 19:30 - 21:00
Q3: 21:00 - 22:30
Q4: 22:30 - 00:00
Micro Quarters (22.5 minutes) (Displayed on 7-minute TF or lower):
Q1: 18:00 - 18:22:30
Q2: 18:22:30 - 18:45
Q3: 18:45 - 19:07:30
Q4: 19:07:30 - 19:30
Features
Time Box Visualization: Highlights different quarters of the trading day to help visualize market phases.
Customizable Colors: Allows users to set different colors for daily, 90-minute, and micro quarters.
Flexible Settings: Designed to work out-of-the-box on both light and dark background charts.
ICT PO3 Alignment: Helps traders align their strategies with ICT's Accumulation, Manipulation, Distribution, and Reversal/Continuation phases.
Usage
Apply this indicator to your NQ1! or ES1! charts and observe the confluence with ICT's macro times. Use it to predict potential market phases and optimize your trading strategy by buying after manipulation down or selling after manipulation up.
Note: The indicator's display may vary based on the timeframe viewed and broker feeds. Back-test and research for best results on your preferred assets.
Targets For Many Indicators [LuxAlgo]The Targets For Many Indicators is a useful utility tool able to display targets for many built-in indicators as well as external indicators. Targets can be set for specific user-set conditions between two series of values, with the script being able to display targets for two different user-set conditions.
Alerts are included for the occurrence of a new target as well as for reached targets.
🔶 USAGE
Targets can help users determine the price limit where the price might start deviating from an indication given by one or multiple indicators. In the context of trading, targets can help secure profits/reduce losses of a trade, as such this tool can be useful to evaluate/determine user take profits/stop losses.
Due to these essentially being horizontal levels, they can also serve as potential support/resistances, with breakouts potentially confirming new trends.
In the above example, we set targets 3 ATR's away from the closing price when the price crosses over the script built-in SuperTrend indicator using ATR period 10 and factor 3. Using "Long Position Target" allows setting a target above the price, disabling this setting will place targets below the price.
Users might be interested in obtaining new targets once one is reached, this can be done by enabling "New Target When Reached" in the target logic setting section, resulting in more frequent targets.
Lastly, users can restrict new target creation until current ones are reached. This can result in fewer and longer-term targets, with a higher reach rate.
🔹 Dashboard
A dashboard is displayed on the top right of the chart, displaying the amount, reach rate of targets 1/2, and total amount.
This dashboard can be useful to evaluate the selected target distances relative to the selected conditions, with a higher reach rate suggesting the distance of the targets from the price allows them to be reached.
🔶 DETAILS
🔹 Indicators
Besides 'External' sources, each source can be set at 1 of the following Build-In Indicators :
ACCDIST : Accumulation/distribution index
ATR : Average True Range
BB (Middle, Upper or Lower): Bollinger Bands
CCI : Commodity Channel Index
CMO : Chande Momentum Oscillator
COG : Center Of Gravity
DC (High, Mid or Low): Donchian Channels
DEMA : Double Exponential Moving Average
EMA : Exponentially weighted Moving Average
HMA : Hull Moving Average
III : Intraday Intensity Index
KC (Middle, Upper or Lower): Keltner Channels
LINREG : Linear regression curve
MACD (macd, signal or histogram): Moving Average Convergence/Divergence
MEDIAN : median of the series
MFI : Money Flow Index
MODE : the mode of the series
MOM : Momentum
NVI : Negative Volume Index
OBV : On Balance Volume
PVI : Positive Volume Index
PVT : Price-Volume Trend
RMA : Relative Moving Average
ROC : Rate Of Change
RSI : Relative Strength Index
SMA : Simple Moving Average
STOCH : Stochastic
Supertrend
TEMA : Triple EMA or Triple Exponential Moving Average
VWAP : Volume Weighted Average Price
VWMA : Volume-Weighted Moving Average
WAD : Williams Accumulation/Distribution
WMA : Weighted Moving Average
WVAD : Williams Variable Accumulation/Distribution
%R : Williams %R
Each indicator is provided with a link to the Reference Manual or to the Build-In Indicators page.
The latter contains more information about each indicator.
Note that when "Show Source Values" is enabled, only values that can be logically found around the price will be shown. For example, Supertrend , SMA , EMA , BB , ... will be made visible. Values like RSI , OBV , %R , ... will not be visible since they will deviate too much from the price.
🔹 Interaction with settings
This publication contains input fields, where you can enter the necessary inputs per indicator.
Some indicators need only 1 value, others 2 or 3.
When several input values are needed, you need to separate them with a comma.
You can use 0 to 4 spaces between without a problem. Even an extra comma doesn't give issues.
The red colored help text will guide you further along (Only when Target is enabled)
Some examples that work without issues:
Some examples that work with issues:
As mentioned, the errors won't be visible when the concerning target is disabled
🔶 SETTINGS
Show Target Labels: Display target labels on the chart.
Candle Coloring: Apply candle coloring based on the most recent active target.
Target 1 and Target 2 use the same settings below:
Enable Target: Display the targets on the chart.
Long Position Target: Display targets above the price a user selected condition is true. If disabled will display the targets below the price.
New Target Condition: Conditional operator used to compare "Source A" and "Source B", options include CrossOver, CrossUnder, Cross, and Equal.
🔹 Sources
Source A: Source A input series, can be an indicator or external source.
External: External source if 'External" is selected in "Source A".
Settings: Settings of the selected indicator in "Source A", entered settings of indicators requiring multiple ones must be comma separated, for example, "10, 3".
Source B: Source B input series, can be an indicator or external source.
External: External source if 'External" is selected in "Source B".
Settings: Settings of the selected indicator in "Source B", entered settings of indicators requiring multiple ones must be comma separated, for example, "10, 3".
Source B Value: User-defined numerical value if "value" is selected in "Source B".
Show Source Values: Display "Source A" and "Source B" on the chart.
🔹 Logic
Wait Until Reached: When enabled will not create a new target until an existing one is reached.
New Target When Reached: Will create a new target when an existing one is reached.
Evaluate Wicks: Will use high/low prices to determine if a target is reached. Unselecting this setting will use the closing price.
Target Distance From Price: Controls the distance of a target from the price. Can be determined in currencies/points, percentages, ATR multiples, ticks, or using multiple of external values.
External Distance Value: External distance value when "External Value" is selected in "Target Distance From Price".
SADROCThe "Smoothed Accumulation/Distribution Rate of Change" (SADROC) indicator draws inspiration from the Chaikin Oscillator's use of accumulation and distribution, formatted in a manner just like the MACD (Moving Average Convergence Divergence) indicator. My goal was to create something with greater speed and accuracy than the classic MACD
Here's a breakdown of its key elements:
Inputs: Users can customize the indicator by specifying the fast length, slow length, and signal length to fit their preferences.
Calculations: The indicator calculates cumulative volume and then computes the Accumulation/Distribution (AD) value based on price and volume data. The SADROC is calculated as the Rate of Change of the exponential moving averages of the price. The difference between these two values is further smoothed to generate the final SADROC value.
Plotting: The indicator plots the SADROC line and a signal line on the chart. Additionally, it includes a histogram that visually represents the difference between SADROC and the signal line.
Grid Spot Trading Algorithm V2 - The Quant ScienceGrid Spot Trading Algorithm V2 is the last grid trading algorithm made by our developer team.
Grid Spot Trading Algorithm V2 is a fixed 10-level grid trading algorithm. The grid is divided into an accumulation area (red) and a selling area (green).
In the accumulation area, the algorithm will place new buy orders, selling the long positions on the top of the grid.
BUYING AND SELLING LOGIC
The algorithm places up to 5 limit orders on the accumulation section of the grid, each time the price cross through the middle grid. Each single order uses 20% of the equity.
Positions are closed at the top of the grid by default, with the algorithm closing all orders at the first sell level. The exit level can be adjusted using the user interface, from the first level up to the fifth level above.
CONFIGURING THE ALGORITHM
1) Add it to the chart: Add the script to the current chart that you want to analyze.
2) Select the top of the grid: Confirm a price level with the mouse on which to fix the top of the grid.
3) Select the bottom of the grid: Confirm a price level with the mouse on which to fix the bottom of the grid.
4) Wait for the automatic creation of the grid.
USING THE ALGORITHM
Once the grid configuration process is completed, the algorithm will generate automatic backtesting.
You can add a stop loss that destroys the grid by setting the destruction price and activating the feature from the user interface. When the stop loss is activated, you can view it on the chart.
VolumeIndicatorsLibrary "VolumeIndicators"
This is a library of 'Volume Indicators'.
It aims to facilitate the grouping of this category of indicators, and also offer the customized supply of the source, not being restricted to just the closing price.
Indicators:
1. Volume Moving Average (VMA):
Moving average of volume. Identify trends in trading volume.
2. Money Flow Index (MFI): Measures volume pressure in a range of 0 to 100.
Calculates the ratio of volume when the price goes up and when the price goes down
3. On-Balance Volume (OBV):
Identify divergences between trading volume and an asset's price.
Sum of trading volume when the price rises and subtracts volume when the price falls.
4. Accumulation/Distribution (A/D):
Identifies buying and selling pressure by tracking the flow of money into and out of an asset based on volume patterns.
5. Chaikin Money Flow (CMF):
A variation of A/D that takes into account the daily price variation and weighs trading volume accordingly.
6. Volume Oscillator (VO):
Identify divergences between trading volume and an asset's price. Ratio of change of volume, from a fast period in relation to a long period.
7. Positive Volume Index (PVI):
Identify the upward strength of an asset. Volume when price rises divided by total volume.
8. Negative Volume Index (NVI):
Identify the downward strength of an asset. Volume when price falls divided by total volume.
9. Price-Volume Trend (PVT):
Identify the strength of an asset's price trend based on its trading volume. Cumulative change in price with volume factor
vma(length, maType, almaOffset, almaSigma, lsmaOffSet)
@description Volume Moving Average (VMA)
Parameters:
length : (int) Length for moving average
maType : (int) Type of moving average for smoothing
almaOffset : (float) Offset for Arnauld Legoux Moving Average
almaSigma : (float) Sigma for Arnauld Legoux Moving Average
lsmaOffSet : (float) Offset for Least Squares Moving Average
Returns: (float) Moving average of Volume
mfi(source, length)
@description MFI (Money Flow Index).
Uses both price and volume to measure buying and selling pressure in an asset.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length
Returns: (float) Money Flow series
obv(source)
@description On Balance Volume (OBV)
Same as ta.obv(), but with customized type of source
Parameters:
source : (float) Series
Returns: (float) OBV
ad()
@description Accumulation/Distribution (A/D)
Returns: (float) Accumulation/Distribution (A/D) series
cmf(length)
@description CMF (Chaikin Money Flow).
Measures the flow of money into or out of an asset over time, using a combination of price and volume, and is used to identify the strength and direction of a trend.
Parameters:
length
Returns: (float) Chaikin Money Flow series
vo(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet)
@description Volume Oscillator (VO)
Parameters:
shortLen : (int) Fast period for volume
longLen : (int) Slow period for volume
maType : (int) Type of moving average for smoothing
almaOffset
almaSigma
lsmaOffSet
Returns: (float) Volume oscillator
pvi(source)
@description Positive Volume Index (PVI)
Same as ta.pvi(), but with customized type of source
Parameters:
source : (float) Series
Returns: (float) PVI
nvi(source)
@description Negative Volume Index (NVI)
Same as ta.nvi(), but with customized type of source
Parameters:
source : (float) Series
Returns: (float) PVI
pvt(source)
@description Price-Volume Trend (PVT)
Same as ta.pvt(), but with customized type of source
Parameters:
source : (float) Series
Returns: (float) PVI
Chaikin Money Flow - LibraryLibrary "Chaikin Money Flow"
cmf()
Developed by Marc Chaikin, Chaikin Money Flow measures the amount of Money Flow Volume over a specific period.
Money Flow Volume forms the basis for the Accumulation Distribution Line. Instead of a cumulative total of
Money Flow Volume, Chaikin Money Flow simply sums Money Flow Volume for a specific look-back period, typically
20 or 21 days. The resulting indicator fluctuates above/below the zero line just like an oscillator. Chartists
weigh the balance of buying or selling pressure with the absolute level of Chaikin Money Flow. Chartists can
also look for crosses above or below the zero line to identify changes on money flow.
The Accumulation Distribution Line was developed by Marc Chaikin to measure the cumulative flow of money into and
out of an index or security. The Accumulation/Distribution Line can be compared to the OBV (On Balance Volume),
which adds or subtracts volume depending on the closing price. Marc Chaikin chose a different approach, instead
of relying on the closing price, he used CLV (Close Location Value).
Crypto Force IndexIntroduction
The Crypto Force Index (CFI) indicator helps us understand the current strength and weakness of the price. It is very useful when used on high timeframes for investment purposes and not for short term trading.
To determine the strength and weakness of the price, a level grid based on the RSI indicator is used.
Based on the RSI value, red circles (oversold condition) and green circles (overbought condition) appear under the price candles. The more intense the color of the circles, the more that the current price is in an overbought or oversold condition.
The signal levels are all configurable to adapt the indicator across multiple instruments and markets.
The default configuration have been designed to obtain more accurate signals on Ethereum and Bitcoin, using the weekly timeframe.
Why Crypto Force Index?
The Crypto Force Index (CFI) is the consequence of my study of investments based on the accumulation plan. I wanted to demonstrate that I am improving the returns of the classic DCA ( dollar cost averaging ) and VA ( value averaging ).
After finding my own model of an accumulation plan, I decided to create the Crypto Force Index to help me visually enter the market.
The formulas of the indicator are very simple, but my studies confirm the power of this tool.
How are the signals to be interpreted?
The Crypto Force Index helps us to highlight the overbought and oversold areas, with the use of circles under the price of candles and with a thermometer inserted at the base of the graph, where all the phases of strength and weakness are highlighted.
As soon as the red circles start to appear on the chart, that may be a good time to enter LONG to the market and start accumulating. If the circles are green, we can consider decreasing the current exposure by selling part of your portfolio, or decide to stay flat.
I personally use these signals on the weekly timeframe, to decide to feed my accumulation plan at the beginning of each month.
I hope it can be of help to you! Please help me improve the Crypto Force Index! :)
Co-relation and St-deviation Strategy - BNB/USDT 15minThis indicator based on statistical analysis. it uses standard deviation and its co-relation to price action to generate signals. and following indicators has been used to calculate standard deviation and its co-relation values. finally it is capable to identify market changes in bottoms to pic most suitable points.
1. Parabolic SAR (parabolic stop and reverse)
2. Supertrend
3. Relative strength index (RSI)
4. Money flow index (MFI)
5. Balance of Power
6. Chande Momentum Oscillator
7. Center of Gravity (COG)
8. Directional Movement Index (DMI)
9. Stochastic
10. Symmetrically weighted moving average with fixed length
11. True strength index (TSI)
12. Williams %R
13. Accumulation/distribution index
14. Intraday Intensity Index
15. Negative Volume Index
16. Positive Volume Index
17. On Balance Volume
18. Price-Volume Trend
19. True range
20. Volume-weighted average price
21. Williams Accumulation/Distribution
22. Williams Variable Accumulation/Distribution
23. Simple Moving Average
24. Exponential Moving Average
25. CCI (commodity channel index)
26. Chop Zone
27. Ease of Movement
28. Detrended Price Oscillator
29. Advance Decline Line
30. Bull Bear Power
Indicators Combination Framework v3 IND [DTU]Hello All,
This script is a framework to analyze and see the results by combine selected indicators for (long, short, longexit, shortexit) conditions.
I was designed this for beginners and users to facilitate to see effects of the technical indicators combinations on the chart WITH NO CODE
You can improve your strategies according the results of this system by connecting the framework to a strategy framework/template such as Pinecoder, Benson, daveatt or custom.
This is enhanced version of my previous indicator "Indicators & Conditions Test Framework "
Currently there are 93 indicators (23 newly added) connected over library. You can also import an External Indicator or add Custom indicator (In the source)
It is possible to change it from Indicator to strategy (simple one) by just remarking strategy parts in the source code and see real time profit of your combinations
Feel free to change or use it in your source
Special thanks goes to Pine wizards: Trading view (built-in Indicators), @Rodrigo, @midtownsk8rguy, @Lazybear, @Daveatt and others for their open source codes and contributions
SIMPLE USAGE
1. SETTING: Show Alerts= True (To see your entries and Exists)
2. Define your Indicators (ex: INDICATOR1: ema(close,14), INDICATOR2: ema(close,21), INDICATOR3: ema(close,200)
3. Define Your Combinations for long & Short Conditions
a. For Long: (INDICATOR1 crossover INDICATOR2) AND (INDICATOR3 < close)
b. For Short: (INDICATOR1 crossunder INDICATOR2) AND (INDICATOR3 > close)
4. Select Strategy/template (Import strategy to chart) that you export your signals from the list
5. Analyze the best profit by changing Indicators values
SOME INDICATORS DETAILS
Each Indicator includes:
- Factorization : Converting the selected indicator to Double, triple Quadruple such as EMA to DEMA, TEMA QEMA
- Log : Simple or log10 can be used for calculation on function entries
- Plot Type : You can overlay the indicator on the chart (such ema) or you can use stochastic/Percentrank approach to display in the variable hlines range
- Extended Parametes : You can use default parameters or you can use extended (P1,P2) parameters regarding to indicator type and your choice
- Color : You can define indicator color and line properties
- Smooth : you can enable swma smooth
- indicators : you can select one of the 93 function like ema(),rsi().. to define your indicator
- Source : you can select from already defined indicators (IND1-4), External Indicator (EXT), Custom Indicator (CUST), and other sources (close, open...)
CONDITION DETAILS
- There are are 4 type of conditions, long entry, short entry, long exit, short exit.
- Each condition are built up from 4 combinations that joined with "AND" & "OR" operators
- You can see the results by enabling show alerts check box
- If you only wants to enter long entry and long exit, just fill these conditions
- If "close on opposite" checkbox selected on settings, long entry will be closed on short entry and vice versa
COMBINATIONS DETAILS
- There are 4 combinations that joined with "AND" & "OR" operators for each condition
- combinations are built up from compare 1st entry with 2nd one by using operator
- 1st and 2nd entries includes already defined indicators (IND1-5), External Indicator (EXT), Custom Indicator (CUST), and other sources (close, open...)
- Operators are comparison values such as >,<, crossover,...
- 2nd entry include "VALUE" parameter that will use to compare 1st indicator with value area
- If 2nd indicator selected different than "VALUE", value are will mean previous value of the selection. (ex: value area= 2, 2nd entry=close, means close )
- Selecting "NONE" for the 1st entry will disable calculation of current and following combinations
JOINS DETAILS
- Each combination will join wiht the following one with the JOIN (AND, OR) operator (if the following one is not equal "NONE")
CUSTOM INDICATOR
- Custom Indicator defines harcoded in the source code.
- You can call it with "CUST" in the Indicator definition source or combination entries source
- You can change or implement your custom indicator by updating the source code
EXTERNAL INDICATOR
- You can import an external indicator by selecting it from the ext source.
- External Indicator should be already imported to the chart and it have an plot function to output its signal
EXPORTING SIGNAL
- You can export your result to an already defined strategy template such as Pine coders, Benson, Daveatt Strategy templates
- Or you can define your custom export for other future strategy templates
ALERTS
- By enabling show alerts checkbox, you can see long entry exits on the bottom, and short entry exits aon the top of the chart
ADDITIONAL INFO
- You can see all off the inputs descriptions in the tooltips. (You can also see the previous version for details)
- Availability to set start, end dates
- Minimize repainting by using security function options (Secure, Semi Secure, Repaint)
- Availability of use timeframes
-
Version 3 INDICATORS LIST (More to be added):
▼▼▼ OVERLAY INDICATORS ▼▼▼
alma(src,len,offset=0.85,sigma=6).-------Arnaud Legoux Moving Average
ama(src,len,fast=14,slow=100).-----------Adjusted Moving Average
accdist().-------------------------------Accumulation/distribution index.
cma(src,len).----------------------------Corrective Moving average
dema(src,len).---------------------------Double EMA (Same as EMA with 2 factor)
ema(src,len).----------------------------Exponential Moving Average
gmma(src,len).---------------------------Geometric Mean Moving Average
highest(src,len).------------------------Highest value for a given number of bars back.
hl2ma(src,len).--------------------------higest lowest moving average
hma(src,len).----------------------------Hull Moving Average.
lagAdapt(src,len,perclen=5,fperc=50).----Ehlers Adaptive Laguerre filter
lagAdaptV(src,len,perclen=5,fperc=50).---Ehlers Adaptive Laguerre filter variation
laguerre(src,len).-----------------------Ehlers Laguerre filter
lesrcp(src,len).-------------------------lowest exponential esrcpanding moving line
lexp(src,len).---------------------------lowest exponential expanding moving line
linreg(src,len,loffset=1).---------------Linear regression
lowest(src,len).-------------------------Lovest value for a given number of bars back.
mcginley(src, len.-----------------------McGinley Dynamic adjusts for market speed shifts, which sets it apart from other moving averages, in addition to providing clear moving average lines
percntl(src,len).------------------------percentile nearest rank. Calculates percentile using method of Nearest Rank.
percntli(src,len).-----------------------percentile linear interpolation. Calculates percentile using method of linear interpolation between the two nearest ranks.
previous(src,len).-----------------------Previous n (len) value of the source
pivothigh(src,BarsLeft=len,BarsRight=2).-Previous pivot high. src=src, BarsLeft=len, BarsRight=p1=2
pivotlow(src,BarsLeft=len,BarsRight=2).--Previous pivot low. src=src, BarsLeft=len, BarsRight=p1=2
rema(src,len).---------------------------Range EMA (REMA)
rma(src,len).----------------------------Moving average used in RSI. It is the exponentially weighted moving average with alpha = 1 / length.
sar(start=len, inc=0.02, max=0.02).------Parabolic SAR (parabolic stop and reverse) is a method to find potential reversals in the market price direction of traded goods.start=len, inc=p1, max=p2. ex: sar(0.02, 0.02, 0.02)
sma(src,len).----------------------------Smoothed Moving Average
smma(src,len).---------------------------Smoothed Moving Average
super2(src,len).-------------------------Ehlers super smoother, 2 pole
super3(src,len).-------------------------Ehlers super smoother, 3 pole
supertrend(src,len,period=3).------------Supertrend indicator
swma(src,len).---------------------------Sine-Weighted Moving Average
tema(src,len).---------------------------Triple EMA (Same as EMA with 3 factor)
tma(src,len).----------------------------Triangular Moving Average
vida(src,len).---------------------------Variable Index Dynamic Average
vwma(src,len).---------------------------Volume Weigted Moving Average
volstop(src,len,atrfactor=2).------------Volatility Stop is a technical indicator that is used by traders to help place effective stop-losses. atrfactor=p1
wma(src,len).----------------------------Weigted Moving Average
vwap(src_).------------------------------Volume Weighted Average Price (VWAP) is used to measure the average price weighted by volume
▼▼▼ NON OVERLAY INDICATORS ▼▼
adx(dilen=len, adxlen=14, adxtype=0).----adx. The Average Directional Index (ADX) is a used to determine the strength of a trend. len=>dilen, p1=adxlen (default=14), p2=adxtype 0:ADX, 1:+DI, 2:-DI (def:0)
angle(src,len).--------------------------angle of the series (Use its Input as another indicator output)
aroon(len,dir=0).------------------------aroon indicator. Aroons major function is to identify new trends as they happen.p1 = dir: 0=mid (default), 1=upper, 2=lower
atr(src,len).----------------------------average true range. RMA of true range.
awesome(fast=len=5,slow=34,type=0).------Awesome Oscilator is an indicator used to measure market momentum. defaults : fast=len= 5, p1=slow=34, p2=type: 0=Awesome, 1=difference
bbr(src,len,mult=1).---------------------bollinger %%
bbw(src,len,mult=2).---------------------Bollinger Bands Width. The Bollinger Band Width is the difference between the upper and the lower Bollinger Bands divided by the middle band.
cci(src,len).----------------------------commodity channel index
cctbbo(src,len).-------------------------CCT Bollinger Band Oscilator
change(src,len).-------------------------A.K.A. Momentum. Difference between current value and previous, source - source . is most commonly referred to as a rate and measures the acceleration of the price and/or volume of a security
cmf(len=20).-----------------------------Chaikin Money Flow Indicator used to measure Money Flow Volume over a set period of time. Default use is len=20
cmo(src,len).----------------------------Chande Momentum Oscillator. Calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
cog(src,len).----------------------------The cog (center of gravity) is an indicator based on statistics and the Fibonacci golden ratio.
copcurve(src,len).-----------------------Coppock Curve. was originally developed by Edwin Sedge Coppock (Barrons Magazine, October 1962).
correl(src,len).-------------------------Correlation coefficient. Describes the degree to which two series tend to deviate from their ta.sma values.
count(src,len).--------------------------green avg - red avg
cti(src,len).----------------------------Ehler s Correlation Trend Indicator by
dev(src,len).----------------------------ta.dev() Measure of difference between the series and its ta.sma
dpo(len).--------------------------------Detrended Price OScilator is used to remove trend from price.
efi(len).--------------------------------Elders Force Index (EFI) measures the power behind a price movement using price and volume.
eom(len=14,div=10000).-------------------Ease of Movement.It is designed to measure the relationship between price and volume.p1 = div: 10000= (default)
falling(src,len).------------------------ta.falling() Test if the `source` series is now falling for `length` bars long. (Use its Input as another indicator output)
fisher(len).-----------------------------Fisher Transform is a technical indicator that converts price to Gaussian normal distribution and signals when prices move significantly by referencing recent price data
histvol(len).----------------------------Historical volatility is a statistical measure used to analyze the general dispersion of security or market index returns for a specified period of time.
kcr(src,len,mult=2).---------------------Keltner Channels Range
kcw(src,len,mult=2).---------------------ta.kcw(). Keltner Channels Width. The Keltner Channels Width is the difference between the upper and the lower Keltner Channels divided by the middle channel.
klinger(type=len).-----------------------Klinger oscillator aims to identify money flow’s long-term trend. type=len: 0:Oscilator 1:signal
macd(src,len).---------------------------MACD (Moving Average Convergence/Divergence)
mfi(src,len).----------------------------Money Flow Index s a tool used for measuring buying and selling pressure
msi(len=10).-----------------------------Mass Index (def=10) is used to examine the differences between high and low stock prices over a specific period of time
nvi().-----------------------------------Negative Volume Index
obv().-----------------------------------On Balance Volume
pvi().-----------------------------------Positive Volume Index
pvt().-----------------------------------Price Volume Trend
ranges(src,upper=len, lower=-5).---------ranges of the source. src=src, upper=len, v1:lower=upper . returns: -1 source=upper otherwise 0
rising(src,len).-------------------------ta.rising() Test if the `source` series is now rising for `length` bars long. (Use its Input as another indicator output)
roc(src,len).----------------------------Rate of Change
rsi(src,len).----------------------------Relative strength Index
rvi(src,len).----------------------------The Relative Volatility Index (RVI) is calculated much like the RSI, although it uses high and low price standard deviation instead of the RSI’s method of absolute change in price.
smi_osc(src,len,fast=5, slow=34).--------smi Oscillator
smi_sig(src,len,fast=5, slow=34).--------smi Signal
stc(src,len,fast=23,slow=50).------------Schaff Trend Cycle (STC) detects up and down trends long before the MACD. Code imported from
stdev(src,len).--------------------------Standart deviation
trix(src,len) .--------------------------the rate of change of a triple exponentially smoothed moving average.
tsi(src,len).----------------------------The True Strength Index indicator is a momentum oscillator designed to detect, confirm or visualize the strength of a trend.
ultimateOsc(len.-------------------------Ultimate Oscillator indicator (UO) indicator is a technical analysis tool used to measure momentum across three varying timeframes
variance(src,len).-----------------------ta.variance(). Variance is the expectation of the squared deviation of a series from its mean (ta.sma), and it informally measures how far a set of numbers are spread out from their mean.
willprc(src,len).------------------------Williams %R
wad().-----------------------------------Williams Accumulation/Distribution.
wvad().----------------------------------Williams Variable Accumulation/Distribution.
HISTORY
v3.01
ADD: 23 new indicators added to indicators list from the library. Current Total number of Indicators are 93. (to be continued to adding)
ADD: 2 more Parameters (P1,P2) for indicator calculation added. Par:(Use Defaults) uses only indicator(Source, Length) with library's default parameters. Par:(Use Extra Parameters P1,P2) use indicator(Source,Length,p1,p2) with additional parameters if indicator needs.
ADD: log calculation (simple, log10) option added on indicator function entries
ADD: New Output Signals added for compatibility on exporting condition signals to different Strategy templates.
ADD: Alerts Added according to conditions results
UPD: Indicator source inputs now display with indicators descriptions
UPD: Most off the source code rearranged and some functions moved to the new library. Now system work like a little bit frontend/backend
UPD: Performance improvement made on factorization and other source code
UPD: Input GUI rearranged
UPD: Tooltips corrected
REM: Extended indicators removed
UPD: IND1-IND4 added to indicator data source. Now it is possible to create new indicators with the previously defined indicators value. ex: IND1=ema(close,14) and IND2=rsi(IND1,20) means IND2=rsi(ema(close,14),20)
UPD: Custom Indicator (CUST) added to indicator data source and Combination Indicator source.
UPD: Volume added to indicator data source and Combination Indicator source.
REM: Custom indicators removed and only one custom indicator left
REM: Plot Type "Org. Range (-1,1)" removed
UPD: angle, rising, falling type operators moved to indicator library
Indicator Functions with Factor and HeikinAshiHello all,
This indicator returns below selected indicators values with entered parameters.
Also you can add factorization, functions candles, function HeikinAshi and more to the plot.
VERSION:
Version 1: returns series only source and Length with already defined default values
Version 2: returns series with source, Length, p1 and p2 parameters according to the indicator definition (ex: )
PARAMETERS p1 p2
for defining multi arguments (See indicators list) indicator input value usable with verison=V2 selected.. ex: for alma( src , len ,offset=0.85,sigma=6), set source=source, len=length, p1=0.85 an p2=6
FACTOR:
Add double triple, Quadruple factors to selected indicator (like converting EMA to 2-DEMA, 3-TEMA, 4-QEMA...)
1-Original
2-Double
3-Triple
4-Quadruple
LOG
Log: Use log, log10 on function entries
PLOTTING:
PType: Plotting type of the function on the screen
Original :use original values
Org. Range (-1,1): usable for indicators between range -1 and 1
Stochastic: Convert indicator values by using stochastic calculation between -1 & 1. (use AT/% length to better view)
PercentRank: Convert indicator values by using Percent Rank calculation between -1 & 1. (use AT/% length to better view)
ST/%: length for plotting Type for stochastic and Percent Rank options
Smooth: Use SWMA for smoothing the function
DISPLAY TYPES
Plot Candles: Display the selected indicator as candle by implementing values
Plot Ind: Display result of indicator with selected source
HeikinAshi: Display Selected indicator candles with Heikin Ashi calculation
INDICATOR LIST:
hide = 'DONT DISPLAY', //Dont display & calculate the indicator. (For my framework usage)
alma = 'alma( src , len ,offset=0.85,sigma=6)', // Arnaud Legoux Moving Average
ama = 'ama( src , len ,fast=14,slow=100)', //Adjusted Moving Average
acdst = 'accdist()', // Accumulation/distribution index.
cma = 'cma( src , len )', //Corrective Moving average
dema = 'dema( src , len )', // Double EMA (Same as EMA with 2 factor)
ema = 'ema( src , len )', // Exponential Moving Average
gmma = 'gmma( src , len )', //Geometric Mean Moving Average
hghst = 'highest( src , len )', //Highest value for a given number of bars back.
hl2ma = 'hl2ma( src , len )', //higest lowest moving average
hma = 'hma( src , len )', // Hull Moving Average .
lgAdt = 'lagAdapt( src , len ,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter
lgAdV = 'lagAdaptV( src , len ,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter variation
lguer = 'laguerre( src , len )', //Ehler's Laguerre filter
lsrcp = 'lesrcp( src , len )', //lowest exponential esrcpanding moving line
lexp = 'lexp( src , len )', //lowest exponential expanding moving line
linrg = 'linreg( src , len ,loffset=1)', // Linear regression
lowst = 'lowest( src , len )', //Lovest value for a given number of bars back.
pcnl = 'percntl( src , len )', //percentile nearest rank. Calculates percentile using method of Nearest Rank.
pcnli = 'percntli( src , len )', //percentile linear interpolation. Calculates percentile using method of linear interpolation between the two nearest ranks.
rema = 'rema( src , len )', //Range EMA (REMA)
rma = 'rma( src , len )', //Moving average used in RSI . It is the exponentially weighted moving average with alpha = 1 / length.
sma = 'sma( src , len )', // Smoothed Moving Average
smma = 'smma( src , len )', // Smoothed Moving Average
supr2 = 'super2( src , len )', //Ehler's super smoother, 2 pole
supr3 = 'super3( src , len )', //Ehler's super smoother, 3 pole
strnd = 'supertrend( src , len ,period=3)', //Supertrend indicator
swma = 'swma( src , len )', //Sine-Weighted Moving Average
tema = 'tema( src , len )', // Triple EMA (Same as EMA with 3 factor)
tma = 'tma( src , len )', //Triangular Moving Average
vida = 'vida( src , len )', // Variable Index Dynamic Average
vwma = 'vwma( src , len )', // Volume Weigted Moving Average
wma = 'wma( src , len )', //Weigted Moving Average
angle = 'angle( src , len )', //angle of the series (Use its Input as another indicator output)
atr = 'atr( src , len )', // average true range . RMA of true range.
bbr = 'bbr( src , len ,mult=1)', // bollinger %%
bbw = 'bbw( src , len ,mult=2)', // Bollinger Bands Width . The Bollinger Band Width is the difference between the upper and the lower Bollinger Bands divided by the middle band.
cci = 'cci( src , len )', // commodity channel index
cctbb = 'cctbbo( src , len )', // CCT Bollinger Band Oscilator
chng = 'change( src , len )', //Difference between current value and previous, source - source.
cmo = 'cmo( src , len )', // Chande Momentum Oscillator . Calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
cog = 'cog( src , len )', //The cog (center of gravity ) is an indicator based on statistics and the Fibonacci golden ratio.
cpcrv = 'copcurve( src , len )', // Coppock Curve. was originally developed by Edwin "Sedge" Coppock (Barron's Magazine, October 1962).
corrl = 'correl( src , len )', // Correlation coefficient . Describes the degree to which two series tend to deviate from their ta. sma values.
count = 'count( src , len )', //green avg - red avg
dev = 'dev( src , len )', //ta.dev() Measure of difference between the series and it's ta. sma
fall = 'falling( src , len )', //ta.falling() Test if the `source` series is now falling for `length` bars long. (Use its Input as another indicator output)
kcr = 'kcr( src , len ,mult=2)', // Keltner Channels Range
kcw = 'kcw( src , len ,mult=2)', //ta.kcw(). Keltner Channels Width. The Keltner Channels Width is the difference between the upper and the lower Keltner Channels divided by the middle channel.
macd = 'macd( src , len )', // macd
mfi = 'mfi( src , len )', // Money Flow Index
nvi = 'nvi()', // Negative Volume Index
obv = 'obv()', // On Balance Volume
pvi = 'pvi()', // Positive Volume Index
pvt = 'pvt()', // Price Volume Trend
rise = 'rising( src , len )', //ta.rising() Test if the `source` series is now rising for `length` bars long. (Use its Input as another indicator output)
roc = 'roc( src , len )', // Rate of Change
rsi = 'rsi( src , len )', // Relative strength Index
smosc = 'smi_osc( src , len ,fast=5, slow=34)', //smi Oscillator
smsig = 'smi_sig( src , len ,fast=5, slow=34)', //smi Signal
stdev = 'stdev( src , len )', //Standart deviation
trix = 'trix( src , len )' , //the rate of change of a triple exponentially smoothed moving average .
tsi = 'tsi( src , len )', //True Strength Index
vari = 'variance( src , len )', //ta.variance(). Variance is the expectation of the squared deviation of a series from its mean (ta. sma ), and it informally measures how far a set of numbers are spread out from their mean.
wilpc = 'willprc( src , len )', // Williams %R
wad = 'wad()', // Williams Accumulation/Distribution .
wvad = 'wvad()' //Williams Variable Accumulation/Distribution
I will update the indicator list when I will update the library
Thanks to tradingview, @RodrigoKazuma for their open source indicators
lib_Indicators_v2_DTULibrary "lib_Indicators_v2_DTU"
This library functions returns included Moving averages, indicators with factorization, functions candles, function heikinashi and more.
Created it to feed as backend of my indicator/strategy "Indicators & Combinations Framework Advanced v2 " that will be released ASAP.
This is replacement of my previous indicator (lib_indicators_DT)
I will add an indicator example which will use this indicator named as "lib_indicators_v2_DTU example" to help the usage of this library
Additionally library will be updated with more indicators in the future
NOTES:
Indicator functions returns only one series :-(
plotcandle function returns candle series
INDICATOR LIST:
hide = 'DONT DISPLAY', //Dont display & calculate the indicator. (For my framework usage)
alma = 'alma(src,len,offset=0.85,sigma=6)', //Arnaud Legoux Moving Average
ama = 'ama(src,len,fast=14,slow=100)', //Adjusted Moving Average
acdst = 'accdist()', //Accumulation/distribution index.
cma = 'cma(src,len)', //Corrective Moving average
dema = 'dema(src,len)', //Double EMA (Same as EMA with 2 factor)
ema = 'ema(src,len)', //Exponential Moving Average
gmma = 'gmma(src,len)', //Geometric Mean Moving Average
hghst = 'highest(src,len)', //Highest value for a given number of bars back.
hl2ma = 'hl2ma(src,len)', //higest lowest moving average
hma = 'hma(src,len)', //Hull Moving Average.
lgAdt = 'lagAdapt(src,len,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter
lgAdV = 'lagAdaptV(src,len,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter variation
lguer = 'laguerre(src,len)', //Ehler's Laguerre filter
lsrcp = 'lesrcp(src,len)', //lowest exponential esrcpanding moving line
lexp = 'lexp(src,len)', //lowest exponential expanding moving line
linrg = 'linreg(src,len,loffset=1)', //Linear regression
lowst = 'lowest(src,len)', //Lovest value for a given number of bars back.
pcnl = 'percntl(src,len)', //percentile nearest rank. Calculates percentile using method of Nearest Rank.
pcnli = 'percntli(src,len)', //percentile linear interpolation. Calculates percentile using method of linear interpolation between the two nearest ranks.
rema = 'rema(src,len)', //Range EMA (REMA)
rma = 'rma(src,len)', //Moving average used in RSI. It is the exponentially weighted moving average with alpha = 1 / length.
sma = 'sma(src,len)', //Smoothed Moving Average
smma = 'smma(src,len)', //Smoothed Moving Average
supr2 = 'super2(src,len)', //Ehler's super smoother, 2 pole
supr3 = 'super3(src,len)', //Ehler's super smoother, 3 pole
strnd = 'supertrend(src,len,period=3)', //Supertrend indicator
swma = 'swma(src,len)', //Sine-Weighted Moving Average
tema = 'tema(src,len)', //Triple EMA (Same as EMA with 3 factor)
tma = 'tma(src,len)', //Triangular Moving Average
vida = 'vida(src,len)', //Variable Index Dynamic Average
vwma = 'vwma(src,len)', //Volume Weigted Moving Average
wma = 'wma(src,len)', //Weigted Moving Average
angle = 'angle(src,len)', //angle of the series (Use its Input as another indicator output)
atr = 'atr(src,len)', //average true range. RMA of true range.
bbr = 'bbr(src,len,mult=1)', //bollinger %%
bbw = 'bbw(src,len,mult=2)', //Bollinger Bands Width. The Bollinger Band Width is the difference between the upper and the lower Bollinger Bands divided by the middle band.
cci = 'cci(src,len)', //commodity channel index
cctbb = 'cctbbo(src,len)', //CCT Bollinger Band Oscilator
chng = 'change(src,len)', //Difference between current value and previous, source - source .
cmo = 'cmo(src,len)', //Chande Momentum Oscillator. Calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
cog = 'cog(src,len)', //The cog (center of gravity) is an indicator based on statistics and the Fibonacci golden ratio.
cpcrv = 'copcurve(src,len)', //Coppock Curve. was originally developed by Edwin "Sedge" Coppock (Barron's Magazine, October 1962).
corrl = 'correl(src,len)', //Correlation coefficient. Describes the degree to which two series tend to deviate from their ta.sma values.
count = 'count(src,len)', //green avg - red avg
dev = 'dev(src,len)', //ta.dev() Measure of difference between the series and it's ta.sma
fall = 'falling(src,len)', //ta.falling() Test if the `source` series is now falling for `length` bars long. (Use its Input as another indicator output)
kcr = 'kcr(src,len,mult=2)', //Keltner Channels Range
kcw = 'kcw(src,len,mult=2)', //ta.kcw(). Keltner Channels Width. The Keltner Channels Width is the difference between the upper and the lower Keltner Channels divided by the middle channel.
macd = 'macd(src,len)', //macd
mfi = 'mfi(src,len)', //Money Flow Index
nvi = 'nvi()', //Negative Volume Index
obv = 'obv()', //On Balance Volume
pvi = 'pvi()', //Positive Volume Index
pvt = 'pvt()', //Price Volume Trend
rise = 'rising(src,len)', //ta.rising() Test if the `source` series is now rising for `length` bars long. (Use its Input as another indicator output)
roc = 'roc(src,len)', //Rate of Change
rsi = 'rsi(src,len)', //Relative strength Index
smosc = 'smi_osc(src,len,fast=5, slow=34)', //smi Oscillator
smsig = 'smi_sig(src,len,fast=5, slow=34)', //smi Signal
stdev = 'stdev(src,len)', //Standart deviation
trix = 'trix(src,len)' , //the rate of change of a triple exponentially smoothed moving average.
tsi = 'tsi(src,len)', //True Strength Index
vari = 'variance(src,len)', //ta.variance(). Variance is the expectation of the squared deviation of a series from its mean (ta.sma), and it informally measures how far a set of numbers are spread out from their mean.
wilpc = 'willprc(src,len)', //Williams %R
wad = 'wad()', //Williams Accumulation/Distribution.
wvad = 'wvad()' //Williams Variable Accumulation/Distribution.
}
f_func(string, float, simple, float, float, float, simple) f_func Return selected indicator value with different parameters. New version. Use extra parameters for available indicators
Parameters:
string : FuncType_ indicator from the indicator list
float : src_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 extra parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 extra parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 extra parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
Returns: float Return calculated indicator value
fn_heikin(float, float, float, float) fn_heikin Return given src data (open, high,low,close) as heikin ashi candle values
Parameters:
float : o_ open value
float : h_ high value
float : l_ low value
float : c_ close value
Returns: float heikin ashi open, high,low,close vlues that will be used with plotcandle
fn_plotFunction(float, string, simple, bool) fn_plotFunction Return input src data with different plotting options
Parameters:
float : src_ indicator src_data or any other series.....
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
Returns: float
fn_funcPlotV2(string, float, simple, float, float, float, simple, string, simple, bool, bool) fn_funcPlotV2 Return selected indicator value with different parameters. New version. Use extra parameters fora available indicators
Parameters:
string : FuncType_ indicator from the indicator list
float : src_data_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 extra parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 extra parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 extra parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
Returns: float Return calculated indicator value
fn_factor(string, float, simple, float, float, float, simple, simple, string, simple, bool, bool) fn_factor Return selected indicator's factorization with given arguments
Parameters:
string : FuncType_ indicator from the indicator list
float : src_data_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
simple : int fact_ Add double triple, Quatr factor to selected indicator (like converting EMA to 2-DEMA, 3-TEMA, 4-QEMA...)
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
Returns: float Return result of the function
fn_plotCandles(string, simple, float, float, float, simple, string, simple, bool, bool, bool) fn_plotCandles Return selected indicator's candle values with different parameters also heikinashi is available
Parameters:
string : FuncType_ indicator from the indicator list
simple : int length_ indicator length
float : p1 parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
bool : plotheikin_ Use Heikin Ashi on Plot
Returns: float
Dual SMA Crossover StrategyDual SMA Crossover Strategy with Advanced Risk Management
This Pine Script strategy utilizes a Dual Simple Moving Average (SMA) Crossover system for identifying trend changes, enhanced with comprehensive money and risk management features.
Strategy Logic
The core of the strategy is based on the interaction of two SMAs: a Fast SMA (default 24 periods) and a Slow SMA (default 48 periods).
Long Entry: Triggered when the Fast SMA crosses above the Slow SMA.
Short Entry: Triggered when the Fast SMA crosses below the Slow SMA.
Exit: Positions are closed when an opposite crossover signal occurs.
All trading decisions are made on the close of the candle to prevent any look-ahead bias, ensuring realistic backtest results.
Key Risk Management Features
Money Management:
Risk Per Trade (%): Defines the maximum percentage of account equity to risk on any single trade (default 2.0%). Position sizing is automatically calculated to ensure this risk limit is not exceeded when the Stop Loss is hit.
Stop Loss (SL):
A fixed Stop Loss (%) (default 0.8%) from the entry price is set immediately upon trade entry to limit potential losses.
Take Profit (TP):
A Risk-Reward Ratio (default 2.0) is used to calculate the Take Profit target. For instance, a 2.0 RRR with a 0.8% SL means a 1.6% TP target.
Advanced Trailing Stop Loss (TSL):
Trailing Stop Start (%): The TSL only activates once the trade reaches a predefined profit percentage (default 1.0%).
Trailing Stop Trail (%): Once activated, the TSL moves to lock in profits by trailing the highest (for long) or lowest (for short) price by a specified percentage (default 0.5%). This ensures that the TSL level never falls below the initial Stop Loss, providing continuous risk protection while allowing for further profit accumulation.
This strategy provides a robust framework for trend-following with built-in risk controls, aiming to protect capital and manage potential gains effectively.
Smooth BTCSPL [GiudiceQuantico] – Dual Smoothed MAsSmooth BTCSPL – Dual Smoothed MAs
What it measures
• % of Bitcoin addresses in profit vs loss (on-chain tickers).
• Spread = profit % − loss % → quick aggregate-sentiment gauge.
• Optional alpha-decay normalisation ⇒ keeps the curve on a 0-1 scale across cycles.
User inputs
• Use Alpha-Decay Adjusted Input (true/false).
• Fast MA – type (SMA / EMA / WMA / VWMA) & length (default 100).
• Slow MA – type & length (default 200).
• Colours – Bullish (#00ffbb) / Bearish (magenta).
Computation flow
1. Fetch daily on-chain series.
2. Build raw spread.
3. If alpha-decay enabled:
alpha = (rawSpread − 140-week rolling min) / (1 − rolling min).
4. Smooth chosen base with Fast & Slow MAs.
5. Bullish when Fast > Slow, bearish otherwise.
6. Bars tinted with the same bull/bear colour.
How to read
• Fast crosses above Slow → rising “addresses-in-profit” momentum → bullish bias.
• Fast crosses below Slow → stress / capitulation risk.
• Price-indicator divergences can flag exhaustion or hidden accumulation.
Tips
• Keep in a separate pane (overlay = false); bar-colouring still shows on price chart.
• Shorter lengths for swing trades, longer for macro outlook.
• Combine with funding rates, NUPL or simple price-MA crossovers for confirmation.
Climax Detector (Buy & Sell)This indicator identifies potential Buying Climax (BC) and Selling Climax (SC) events based on volume spikes relative to historical averages.
• Buying Climax (BC):
• Detected when a green candle forms with volume significantly higher than the average (default: 2×).
• Often signals the end of an uptrend or distribution phase.
• Selling Climax (SC):
• Detected when a red candle forms with very high volume (default: 2× average).
• Often occurs at the end of a downtrend, suggesting panic selling and potential accumulation.
How it works:
• Calculates a moving average of volume over a user-defined period (default: 20 candles)
• Flags a climax when current volume exceeds the defined multiplier (default: 2.0×)
• Marks:
• BC with an orange triangle above the bar
• SC with a fuchsia triangle below the bar
Customizable Settings:
• Volume spike sensitivity
• Lookback period for average volume
Use Cases:
• Spot possible trend exhaustion
• Confirm Wyckoff phases
• Combine with support/resistance for reversal entries
Disclaimer: This tool is designed to assist in identifying high-probability exhaustion zones but should be used alongside other confirmations or strategies.
Fibonacci Volume Profiles [AlgoAlpha]Unlock a deeper understanding of price action with the Fibonacci Volume Profiles indicator by AlgoAlpha! This powerful tool blends Fibonacci retracement levels with customizable volume profiles, helping traders identify high-probability areas of support, resistance, and accumulation. Designed for both continuous dynamic levels and custom time periods, this indicator is a must-have for traders seeking confluence in market structure analysis.
🔑 Key Features
📈 Dual Mode Selection : Choose between Continuous Fibonacci levels, which adapt dynamically to pivots, or a Custom Period mode, where you set your own start and end points.
📊 Integrated Volume Profile : Visualize volume distributions at key Fibonacci retracement levels, revealing areas of strong buying/selling interest.
🎨 Customizable Colors & Transparency : Adjust Fibonacci level colors, fill zones, and profile transparency for a visually clear experience.
🔍 Profile Resolution & Scaling : Control the number of price levels and width of the volume profile for detailed market insights.
🛠 Extendable Levels : Optionally extend Fibonacci levels to the right of the chart for better visualization of future price interaction.
📌 How to Use
Add the Indicator: Click on the star icon to add it to your favorites and apply it to your TradingView chart.
Analyze The Market: Observe how price interacts with Fibonacci levels alongside the volume profile to confirm support/resistance zones. Switch between custom range or continuous mode to align the tool with your trading style.
⚙️ How It Works
The indicator calculates pivot highs/lows dynamically (or uses user-defined time periods) to plot Fibonacci retracement levels. It then builds a volume profile by analyzing historical volume data, grouping it into price bins to highlight volume-heavy zones. The Point of Control (PoC) is identified as the level with the highest traded volume, acting as a key price magnet. The color-coded Fibonacci levels help traders spot retracement zones, while the volume profile confirms strength or weakness in those areas.
Liquidity Heatmap & Volume-Weighted RSILiquidity Heatmap Indicator with Volume-Weighted RSI
Description:
The Liquidity Heatmap Indicator with Volume-Weighted RSI (VW-RSI) is a powerful tool designed for traders to visualize market liquidity zones while integrating a volume-adjusted momentum oscillator. This indicator provides a dynamic heatmap of liquidity levels across various price points and enhances traditional RSI by incorporating volume weight, making it more responsive to market activity.
Key Features:
Liquidity Heatmap Visualization: Identifies high-liquidity price zones, allowing traders to spot potential areas of support, resistance, and accumulation.
Volume-Weighted RSI (VW-RSI): Enhances the RSI by factoring in trading volume, reducing false signals and improving trend confirmation.
Customizable Sensitivity: Users can adjust parameters to fine-tune heatmap intensity and RSI smoothing.
Dynamic Market Insights: Helps identify potential price reversals and trend strength by combining liquidity depth with momentum analysis.
How to Use:
1. Identify Liquidity Zones: The heatmap colors indicate areas of high and low liquidity, helping traders pinpoint key price action areas.
2. Use VW-RSI for Confirmation: When VW-RSI diverges from price near a liquidity cluster, it signals a potential reversal or continuation.
3. Adjust Parameters: Fine-tune the RSI period, volume weighting, and heatmap sensitivity to align with different trading strategies.
This indicator is ideal for traders who rely on order flow analysis, volume-based momentum strategies, and liquidity-driven trading techniques.
Volume Distribution Before/After Top
Description
This script visualizes the distribution of volume before and after a price peak within a specified time interval. The green area represents the volume accumulated before the peak, and the red area represents the volume accumulated after the peak. The script also calculates and displays the volume-weighted average price (VWAP) on each side of the peak with a dotted line and a label.
The key features include:
Volume Visualization: Transparent green and red bars indicate volume fractions before and after the peak.
VWAP Markers: Centered labels with VWAP values are plotted above the corresponding levels.
Interactive Inputs: Define the start and end points of the analysis interval using customizable anchor times.
This tool is ideal for traders who want to analyze how volume dynamics are distributed around key price levels. It can help identify potential zones of support and resistance and improve the understanding of market behavior in response to volume accumulation.
Instructions
Select the start and end anchor times using the input fields.
Observe the volume distribution and VWAP levels on the chart.
Use the visual data to make more informed trading decisions.
Crypto SeasonDefinition
This indicator is an informative indicator aiming to predict when the Altcoin season will start and when Bitcoin will enter the month season.
The average of the graph shows the dominance of altcoins other than BTC, ETH and USDT. If this value is over 30, the BTC says that the bull season is over. This value indicates that 20 to 30 BTC is in the bull season or accumulation. If this value is less than 20, it means that the subcoin season has begun.
Disclaimer
This indicator is for informational purposes only and should be used for educational purposes only. You may lose money if you rely on this to trade without additional information. Use at your own risk.
Version
v1.0
Liquidity Swings [UAlgo]The "Liquidity Swings " indicator is designed to help traders identify liquidity swings within the market. This tool is particularly useful for visualizing areas where liquidity is accumulating and where it is being swept, providing valuable insights for making informed trading decisions. By tracking the pivots in price and associating them with volume, the indicator highlights zones of potential support and resistance, helping traders understand market dynamics more clearly.
🔶 Key Features
Liquidity Swing Sensitivity: Adjustable sensitivity settings to fine-tune the detection of liquidity swings according to market conditions and trader preferences.
Two modes of liquidity calculation:
Cumulative Liquidity: Aggregates unswept liquidity over multiple swings until it is swept, providing a broader view of liquidity accumulation.
Individual Liquidity: Displays the accumulated liquidity for each swing independently, offering a more granular perspective.
Visual Customization: Options to customize the colors and sizes of liquidity lines, areas, and informational text for better visual clarity.
Dynamic Updates: The indicator dynamically updates liquidity zones and labels, adjusting to new market data to keep traders informed in real-time.
🔶 Disclaimer
The "Liquidity Swings " indicator is provided for educational and informational purposes only.
It should not be considered as financial advice or a recommendation to buy or sell any financial instrument.
The use of this indicator involves inherent risks, and users should employ their own judgment and conduct their own research before making any trading decisions. Past performance is not indicative of future results.
🔷 Related Scripts
Liquidity Sweeps
Williams %R Liquidity Sweeps
Bitcoin Wave RainbowThis Bitcoin Wave Rainbow model is a powerful tool designed to help traders of all levels understand and navigate the Bitcoin market. It works only with BTC in any timeframe, but better looks in dayly or weekly timeframes. It provides valuable insights into historical price behavior and offers forecasts for the next decade, making it an essential asset for both short-term and long-term strategies.
How the Model Works
The model is built on a logarithmic trend, also known as a power law, represented by the green line on the chart. This line illustrates the expected price trajectory of Bitcoin over time. The model also incorporates a range of price fluctuations around this trend, represented by colored bands.
The width of these bands narrows over time, indicating that the model becomes increasingly accurate as it progresses. This is due to the exponential decrease in the range of price fluctuations, making the model a reliable tool for predicting future price movements.
Understanding the Zones
Blue Zone: This zone signifies that the price is below its trend, making it a recommended area for buying Bitcoin. It represents a level where the price is unlikely to fall further, providing a potential opportunity for accumulation.
Green Zone: This zone represents a fair price range, where the price is relatively close to its trend. In this zone, the price may continue to go up or down, depending on the halving season. ransiting up around any halving and transiting down around 2 years after each halving.
Yellow Zone: This zone indicates that the price is somewhat overheated, often due to the hype following a halving event. While there may still be room for the price to rise, traders should exercise caution in this zone, as a price correction could occur.
Red Zone: This zone represents a strong overbought condition, where the price is significantly above its trend. Traders should be extremely cautious in this zone and consider reducing their positions, as the price is likely to revert back towards the trend or even lower.
Using the Model in Your Trading Strategy
This indicator can be used in conjunction with the Bitcoin Wave Model, which complements it by showing harmonic price fluctuations associated with halving events. Together, these indicators provide a comprehensive view of the Bitcoin market, allowing traders to make informed decisions based on both historical data and future projections.
Benefits for Traders
This Bitcoin price model offers numerous benefits for traders, including:
Clear Visualization: The model provides a clear and concise visual representation of Bitcoin's price behavior, making it easy to understand and interpret.
Accurate Forecasting: The model's accuracy increases over time, providing reliable forecasts for future price movements.
Risk Management: The model helps traders identify overbought and oversold conditions, allowing them to manage their risk more effectively.
Strategic Decision-Making: By understanding the different zones and their implications, traders can make more informed decisions about when to buy, sell, or hold Bitcoin.
By incorporating this Bitcoin price model into your trading strategy, you can gain a deeper understanding of the market dynamics and improve your chances of success.
VWAP DivergenceThe "VWAP Divergence" indicator leverages the VWAP Rolling indicator available in TradingView's library to analyze price and volume dynamics. This custom indicator calculates a rolling VWAP (Volume Weighted Average Price) and compares it with a Simple Moving Average (SMA) over a specified historical period.
Advantages:
1. Accurate VWAP Calculation: The VWAP Rolling indicator computes a VWAP that dynamically adjusts based on recent price and volume data. VWAP is a vital metric used by traders to understand the average price at which a security has traded, factoring in volume.
2. SMA Comparison: By contrasting the rolling VWAP from the VWAP Rolling indicator with an SMA of the same length, the indicator highlights potential divergences. This comparison can reveal shifts in market sentiment.
3. Divergence Identification: The primary purpose of this indicator is to detect divergences between the rolling VWAP from VWAP Rolling and the SMA. Divergence occurs when the rolling VWAP significantly differs from the SMA, indicating potential changes in market dynamics.
Interpretation:
1. Positive Oscillator Values: A positive oscillator (difference between rolling VWAP and SMA) suggests that the rolling VWAP, derived from the VWAP Rolling indicator, is above the SMA. This could indicate strong buying interest or accumulation.
2. Negative Oscillator Values: Conversely, a negative oscillator value indicates that the rolling VWAP is below the SMA. This might signal selling pressure or distribution.
3. Divergence Signals: Significant divergences between the rolling VWAP (from VWAP Rolling) and SMA can indicate shifts in market sentiment. For instance, a rising rolling VWAP diverging upwards from the SMA might suggest increasing bullish sentiment.
4. Confirmation with Price Movements: Traders often use these divergences alongside price action to confirm potential trend reversals or continuations.
Implementation:
1. Length Parameter: Adjust the Length input to modify the lookback period for computing both the rolling VWAP from VWAP Rolling and the SMA. A longer period provides a broader view of market sentiment, while a shorter period is more sensitive to recent price movements.
2. Visualization: The indicator plots the VWAP SMA Oscillator, which visually represents the difference (oscillator) between the rolling VWAP (from VWAP Rolling) and SMA over time.
3. Zero Line: The zero line (gray line) serves as a reference point. Oscillator values crossing above or below this line can be interpreted as bullish or bearish signals, respectively.
4. Contextual Analysis: Interpret signals from this indicator in conjunction with broader market conditions and other technical indicators to make informed trading decisions.
This indicator, utilizing the VWAP Rolling component, is valuable for traders seeking insights into the relationship between volume-weighted price levels and traditional moving averages, aiding in the identification of potential trading opportunities based on market dynamics.
Volume-Blended Candlesticks [QuantVue]Introducing the Volume-Blended Candlestick Indicator, a powerful tool that seamlessly integrates volume information with candlesticks, providing you with a comprehensive view of market dynamics in a single glance.
The Volume-Blended Candlestick Indicator employs a unique approach of projecting volume totals by calculating the total volume traded per second and comparing it to the time left in the session as well as the historical average length selected by the user.
The indicator then dynamically adjusts the opacity of the candlestick colors based on the intensity of the projected volume. As volume intensifies, the candlestick colors become more pronounced, while low volume will cause colors to fade allowing you to visually perceive the level of buying or selling.
One of the standout features of the Volume-Blended Candlestick Indicator is its ability to identify pocket pivots. A pocket pivot is an up day with volume greater than any of the down days volume in the past 10 days. By highlighting these pocket pivots on your chart, the indicator helps you identify potential stealth accumulation.
In addition to blending volume with candlesticks and spotting pocket pivots, this versatile indicator provides you with an insightful table displaying key volume metrics. The table includes the average volume, average dollar volume, and the up-down volume ratio, allowing you to get a clear picture of buying and selling pressure.
Settings Include:
🔹Sensitivty Level: Normal, More, Less
🔹Volume MA Length
🔹Toggle Color based on previous close
🔹Show or hide volume info
🔹Chose candlestick colors
🔹Show or hide pocket pivots
🔹Show or hide volume info table
Don't hesitate to reach out with any questions or concerns.
We hope you enjoy!
Cheers.
